Electron Energy-loss Spectroscopy Spectrum Imaging Research Articles

Spectral mixture analysis of EELS spectrum-images

Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, Earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types…) present in an observed scene and to estimate their respective proportions in each mixed pixel of the acquired image. This task is usually referred to as spectral mixture analysis or spectral unmixing (SU). SU aims at decomposing the measured pixel spectrum into a collection of constituent spectra, called endmembers, and a set of corresponding fractions (abundances) that indicate the proportion of each endmember present in the pixel. Similarly, when processing spectrum-images, microscopists usually try to map elemental, physical and chemical state information of a given material. This paper reports how a SU algorithm dedicated to remote sensing hyperspectral images can be successfully applied to analyze spectrum-image resulting from electron energy-loss spectroscopy (EELS). SU generally overcomes standard limitations inherent to other multivariate statistical analysis methods, such as principal component analysis (PCA) or independent component analysis (ICA), that have been previously used to analyze EELS maps. Indeed, ICA and PCA may perform poorly for linear spectral mixture analysis due to the strong dependence between the abundances of the different materials. One example is presented here to demonstrate the potential of this technique for EELS analysis.

A quantitative analysis of a multi-phase polycrystalline cubic boron nitride tool material using DualEELS

This paper presents a quantitative analysis of a polycrystalline cubic boron nitride tool material by electron energy-loss spectroscopy spectrum imaging acquired in dual range mode. Having both the low-loss and core-loss regions acquired nearly simultaneously provides the advantage of accurate corrections for thickness effects and thus the possibility to perform quantification calculations. This has resulted in extracted bonding maps with areal (atoms/nm 2) or volumetric (atoms/nm 3) densities. Spectroscopic signatures in the low-loss and core-loss energy ranges, of the elements (Al, B, C, N, Ti and O) present in the existing phases, were studied and used when extracting the element specific bonding maps by the multiple linear least squares fitting procedure. Variations of elemental concentrations across the investigated area were determined, despite of phase overlap in the beam direction or energy overlaps in the EELS spectrum. Moreover, the surface oxidation of Ti(C,N) and AlN as well as the amorphisation of α-Al 2O 3 is discussed.

A TEM nanoanalytical investigation of Pd/Ge ohmic contacts for the miniaturization and optimization of n-InGaAs MOSFET devices

In this paper, a nanoanalytical investigation of electron beam evaporated PdGe ohmic contacts onto an n+ In0.53Ga0.47As layer using electron energy loss spectroscopy (EELS) is presented. The chemical information reported in this paper has been obtained using EELS spectrum images (SI) that allow not only depth resolution but also spatial resolution which is essential in such inhomogeneous systems.

Three-dimensional electron microscopy of individual nanoparticles

The characterization of nanomaterials with complex three-dimensional (3D) geometries is required to further research and enable the continuing development of nanotechnology. In this manuscript, we report a protocol which combines focused ion beam (FIB) milling, thin film deposition and solution chemistry to optimize a rotation holder for 3D structural and chemical analysis of nanoparticles. This protocol is used to customize the geometry, surface and chemistry of a scanning transmission electron microscope (STEM) or transmission electron microscope (TEM) rotation holder for the nanoparticle system of interest. To illustrate this concept, rotation holder stubs were optimized to facilitate the 3D STEM imaging and analysis of core-shell nanoparticles used for DNA detection. Using this approach, it was possible to characterize the morphology, optoelectronic properties and chemical composition of individual core-shell nanoparticles in 3D. STEM images were captured at regular angular intervals over a complete 360 degrees rotation to eliminate missing wedge artifacts. Electron energy-loss spectroscopy (EELS) spectrum images were acquired intermittently for comparative chemical analysis. This approach allows the 3D STEM/TEM analysis to be performed with the nanoparticle of interest cantilevered over vacuum to minimize substrate effects. Standard tomography techniques were used to reconstruct the 3D structure of the individual nanoparticles from the STEM HAADF rotation series. EELS spectrum imaging was used to determine the local material properties such as composition, band-gap and plasmon energy. The nanoparticle analysis protocol reported here can easily be adapted to facilitate 3D TEM/STEM analysis of other nanomaterial systems.

TEM Characterization of Nanostructured MgAl2O4 Synthesized by a Direct Conversion Process from γ‐Al2O3

Nanostructured MgAl2O4 spinel was synthesized by a direct conversion process from cubic γ‐Al2O3. The effect of post‐annealing temperature (300°, 500°, and 800°C) on MgAl2O4 phase formation was investigated using transmission electron microscopy, selected area electron diffraction (SAED), electron energy loss spectroscopy (EELS), and energy‐dispersive spectroscopy (EDS). Relative diffraction intensities as well as lattice parameter measurements from SAED revealed that MgAl2O4 spinel structure starts forming at temperatures as low as 300°C. EELS and EDS spectrum images also revealed an increase in elemental homogeneity with increasing annealing temperature. The degree of ordering of Mg and Al between octahedral and tetrahedral sites has been determined from relative diffraction intensities. Results show that annealing to 800°C leads to a spinel phase with an order parameter of 0.78.

Comparison of STEM EELS Spectrum Imaging vs EFTEM Spectrum Imaging

Abstract Electron energy-loss spectroscopy (EELS) in the transmission electron microscope (TEM) analyzes the energy distribution of the probe electrons after they have lost energy within the sample. The resultant energy-losses are characteristic of elemental, chemical, and dielectric properties and are typically measured in one of two ways. Parallel-detection EELS spectrometers (PEELS) acquire large energy ranges of the energy-loss spectrum simultaneously for rapid acquisition of spectral data at a single area. In contrast, the energy filtering TEM (EFTEM) acquires only a single energy band at once, but does so for thousands or even millions of image pixels simultaneously. Spectrum imaging (SI) involves acquisition of detailed spectroscopic data sufficient for rigorous analysis at each pixel in a digital image. (Fig. la) A STEM EELS spectrum image “data cube” can be acquired by stepping a focused electron probe to each pixel and filling the spectrum image one spectrum at a time.

EFTEM and STEM EELS Spectrum Imaging

Abstract Electron energy-loss spectroscopy (EELS) in the transmission electron microscope (TEM) is a powerful technique that analyzes the inelastic scattering distribution of the fast TEM electrons after they have lost energy within the sample. The resultant energy-losses are characteristic of elemental, chemical, and dielectric properties and are typically measured in one of two ways. Parallel-detection EELS spectrometers (PEELS) acquire spectral data over a large range of energy-loss simultaneously for rapid acquisition of spectral data at a single point. In contrast, the energy filtering TEM (EFTEM) acquires only a single energy band at once, but does so for thousands or even millions of image pixels simultaneously. Spectrum-imaging concerns the acquisition of spectroscopic data of sufficient detail for rigorous analysis at each pixel in a digital image. (Fig. 1) A STEM EELS spectrum image “data cube” can be acquired by stepping a focused electron probe to each pixel and filling the spectrum image one spectrum at a time.

Electron energy-loss spectrum-imaging

Electron energy-loss spectroscopy (EELS) in the scanning transmission electron microscope (STEM) is a powerful method for analyzing elemental, chemical, dielectric, and other information. The technique can be extended to produce quantitative images useful for interpreting the spatial distribution of this information. This paper describes an implementation of a new method of quantitative mapping termed “spectrum-imaging”. The resultant “spectrum-images” consist of complete spectra stored at each pixel in a scanned image. This allows not only the data in each spectrum to be analyzed a posteriori using time-consuming methods, but also permits the spatial statistics of the collective spectra to be exploited. Spectrum-image processing is fundamentally different from previous quantitative image processing that has been performed “on-the-fly”. The methods used to acquire and process EELS spectrum-images are here described, along with a range of applications and examples of the technique.